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import os
from googleapiclient.discovery import build
from lang import G4F
from fastapi import FastAPI, Request, Path
from pydantic import BaseModel
from fastapi.middleware.cors import CORSMiddleware
from ImageCreator import generate_image_prodia
app = FastAPI()
app.add_middleware( # add the middleware
CORSMiddleware,
allow_credentials=True, # allow credentials
allow_origins=["*"], # allow all origins
allow_methods=["*"], # allow all methods
allow_headers=["*"], # allow all headers
)
google_api_key = os.environ["GOOGLE_API_KEY"]
cse_id = os.environ["GOOGLE_CSE_ID"]
model = os.environ['default_model']
def search_google(query):
service = build("customsearch", "v1", developerKey=google_api_key)
result = service.cse().list(
q=query,
cx=cse_id
).execute()
return result['items']
@app.get("/")
def hello():
return "Hello! My name is Linlada."
def gpt_with_google_search(prompt):
search_results = search_google(prompt)
text = ""
ref = ""
for item in search_results:
text += item['title'] + "\n" + item['snippet'] + "\n\n"
ref += "- {} ({})\n".format(item['title'], item['link'])
results = generate_text(f'Summarize: {text}')
res = "{} \n\n {}".format(results, ref)
return res
def gpt_with_google_search(prompt):
search_results = search_google(prompt)
text = ""
ref = ""
ref_count = 1
for item in search_results:
text += item['title'] + "\n" + item['snippet'] + "\n\n"
ref += " [{}] {} ({})\n".format(ref_count, item['title'], item['link'])
ref_count += 1
results = generate_text(f'Summarize: {text}')
res = "{} \n\n{}".format(results, ref)
return res
class Linlada(BaseModel):
prompt: str
web_access: str
model: str = 'gpt-3.5-turbo'
@app.post('/linlada')
def linlada(request: Linlada):
prompt = request.prompt
model = request.model
web_access = request.web_access
llm = G4F(model=model)
if web_access == "true":
chat = gpt_with_google_search(prompt)
else:
chat = llm(prompt)
return chat
class User(BaseModel):
prompt: str
model: str = None
sampler: str = None
seed: int = None
neg: str = None
@app.post("/imagen")
def generate_image(request: User):
prompt = request.prompt
model = request.model
sampler = request.sampler
seed = request.seed
neg = request.neg
response = generate_image_prodia(prompt, model, sampler, seed, neg)
return {"image": response}
details = {
1: {'Absolute Reality V1.6': 'absolutereality_V16.safetensors [37db0fc3]',
'Analog V1': 'analog-diffusion-1.0.ckpt [9ca13f02]',
'Anything V3': 'anythingv3_0-pruned.ckpt [2700c435]',
'Anything V4.5': 'anything-v4.5-pruned.ckpt [65745d25]',
'Anything V5': 'anythingV5_PrtRE.safetensors [893e49b9]',
'AbyssOrangeMix V3': 'AOM3A3_orangemixs.safetensors [9600da17]',
'Deliberate V2': 'deliberate_v2.safetensors [10ec4b29]',
'Dreamlike Diffusion V1': 'dreamlike-diffusion-1.0.safetensors [5c9fd6e0]',
'Dreamlike Diffusion V2': 'dreamlike-diffusion-2.0.safetensors [fdcf65e7]',
'Dreamshaper 6 baked vae': 'dreamshaper_6BakedVae.safetensors [114c8abb]',
'Dreamshaper 7': 'dreamshaper_7.safetensors [5cf5ae06]',
'Dreamshaper 8': 'dreamshaper_8.safetensors [9d40847d]',
'Eimis Anime Diffusion V1.0': 'EimisAnimeDiffusion_V1.ckpt [4f828a15]',
"Elldreth's Vivid": 'elldreths-vivid-mix.safetensors [342d9d26]',
'Lyriel V1.6': 'lyriel_v16.safetensors [68fceea2]',
'MechaMix V1.0': 'mechamix_v10.safetensors [ee685731]',
'MeinaMix Meina V9': 'meinamix_meinaV9.safetensors [2ec66ab0]',
'MeinaMix Meina V11': 'meinamix_meinaV11.safetensors [b56ce717]',
'Openjourney V4': 'openjourney_V4.ckpt [ca2f377f]',
'Portrait+ V1': 'portraitplus_V1.0.safetensors [1400e684]',
'Realistic Vision V1.4': 'Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]',
'Realistic Vision V4.0': 'Realistic_Vision_V4.0.safetensors [29a7afaa]',
'Realistic Vision V5.0': 'Realistic_Vision_V5.0.safetensors [614d1063]',
'Redshift Diffusion V1.0': 'redshift_diffusion-V10.safetensors [1400e684]',
'ReV Animated V1.2.2': 'revAnimated_v122.safetensors [3f4fefd9]',
'SD V1.4': 'sdv1_4.ckpt [7460a6fa]',
'SD V1.5': 'v1-5-pruned-emaonly.ckpt [81761151]',
"Shonin's Beautiful People V1.0": 'shoninsBeautiful_v10.safetensors [25d8c546]',
"TheAlly's Mix II": 'theallys-mix-ii-churned.safetensors [5d9225a4]',
'Timeless V1': 'timeless-1.0.ckpt [7c4971d4]'
},
2: {
'Euler': 'Euler',
'Euler a': 'Euler a',
'Heun': 'Heun',
'DPM++ 2M Karras': 'DPM++ 2M Karras',
'DPM++ SDE Karras': 'DPM++ SDE Karras',
'DDIM': 'DDIM'
}
}
@app.get("/imagen-details/{detail_id}")
def image_detail(detail_id: int = Path(None, description="The ID of 1.model id and 2.sampler id", gt=0, lt=3)):
return details[detail_id]
class Test(BaseModel):
prompt: str
model: str = 'gpt-3.5-turbo'
neg: str = False
@app.post("/test")
def test(request: Test):
return {'data': f'Prompt is {request.prompt} Model is {request.model} Neg is {request.neg}'}
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